Paused STP 231 2022 Spring B 20713 Tran (1) Homework: HW 19: Ch 10 - Bivariate Question 1, HW Score: 0%, E 10.1.1 0 of 15 points Data and Linear Part 2 of 3 O Points: 0 of Save Correlati Twenty different statistics students are randomly selected. For each of them, their body temperature ("C) is measured and their head circumference (cm) is measured. a. For this sample of paired data, what does r represent, and what does p represent? b. Without doing any research or calculations, estimate the value of r. c. Does r change if body temperatures are converted to Fahrenheit degrees? using all of the paired data in the population of all statistics students, and p is a statistic that represents the value of the linear correlation coefficient computed from the paired sample data. r is a statistic that represents the value of the linear correlation coefficient computed from the paired sample data, and p is a parameter that represents the value of the linear correlation coefficient that would be computed by using all of the paired data in the population of all statistics students. r is a statistic that represents the value of the linear correlation coefficient computed from the paired sample data, and p is a parameter that represents the proportion of the variation in head circumference that can be explained by variation in body temperature. b. Select the correct choice below and fill in the answer box to complete your choice. (Type an integer or a decimal rounded to one decimal place as needed.) OA. The value of r is estimated to be because it is likely that body temperature and head circumference are strongly negatively correlated. B. The value of r is estimated to be , because it is likely that body temperature and head circumference are strongly positively correlated. O C. The value of r is estimated to be , because it is likely that there is no correlation between body temperature and head circumference Get more help - Clear all 27 MacBoE Homework: HW 19: Ch 10 - Bivariate Data and Question 4, 10.1.4 Linear Correlati Match these values of r with the accompanying scatterplots: -0.364, 0.737, 1, 0.997, and 0.364. Click the icon to view the scatterplots. X Scatterplots Match the values of r to the scatterplots. Scatterplot 1 Scatterplot 2 Scat Scatterplot 1, r = Scatterplot 2, r = Scatterplot 3, r = Scatterplot 4, r = 4- Scatterplot 5, r = 2-1 0 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 Scatterplot 4 Scatterplot 5 0.737 157 14- 13- 0.364 12- 0.997 10-+ 0 02 04 0.6 0.8 0.2 0 4 0.6 0.8 -0.364 Print Done Help me solve this View an example Get more help -As Pearson Access Assignments Do Homework - HW 19: Ch 10 - x * Course Hero X New Tab X + C a mylab.pearson.com/Student/PlayerHomework.aspx?homeworkld=622871013&questionld=1&flushed=false&cld=6914052¢erwin=yes * 0 Paused STP 231 2022 Spring B 20713 Tran (1) Maryana Tymkiv 04/27/22 6:21 PM Homework: HW 19: Ch 10 - Bivariate Data and Question 5, 10.1.9 HW Score: 15.56%, 2.33 of 15 points Linear Correlati Part 2 of 4 O Points: 0 of 1 Save Use the given data set to complete parts (a) through (c) below. (Use a = 0.05.) 10 8 13 9 11 14 6 4 12 5 9.13 8.13 8.73 8.78 9.26 8.09 6.13 3.11 9.13 7.25 4.73 Click here to view a table of critical values for the correlation coefficient. X Table of Critical Values a. Construct a scatterplot. Choose the correct graph below. O A. O B. OC. n 4 =.05 c = .01 10- 10- 950 990 8- .878 959 .811 917 7 .754 .875 8 .707 834 9 666 798 16 10 632 765 602 735 b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. 12 576 708 553 684 The linear correlation coefficient is r = 13 14 661 (Round to three decimal places as needed.) 532 15 514 641 16 497 623 17 482 606 18 468 590 456 575 20 444 561 25 .396 505 30 361 463 35 335 430 40 312 402 45 294 .378 150 .279 361 Help me solve this View an example Get more help - MacBook Air-> C ( mylab.pearson.com/Student/PlayerHomework.aspx?homeworkld=622871013&questionld=1&flushed=false&cld=6914052¢erwin=yes # 0 Paused : STP 231 2022 Spring B 20713 Tran (1) Maryana Tymkiv 04/27/22 6:21 PM (? Homework: HW 19: Ch 10 - Bivariate Data and Question 6, 10.1.15-T HW Score: 17.22%, 2.58 of 15 points Linear Correlati Part 2 of 7 Points: 0 of 1 Save Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths, foot lengths, and heights of males. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Based on these results, does it appear that police can use a shoe print length to estimate the height of a male? Use a significance level of a = 0.05. Shoe Print (cm) 28.8 28.8 31.9 32.4 27.5 Foot Length (cm) | 26.5 25.8 27.7 26.6 26.0 Height (cm) 181.6 179.5 178.5 180.9 171.8 Construct a scatterplot. Choose the correct graph below. DA. VE C O D. 200 200 200 Height (cm Height (cm) Height (cm) Height (cm 60 60 25 35 25 25 Shoe Print (cm) Shoe Print (om) Shoe Print (cm) Shoe Print (cm) The linear correlation coefficient is r =. (Round to three decimal places as needed.) Clear all Check answer Help me solve this View an example Get more help - MacBook Air esc 9- F2. 20 F3, 12- F6 44 40)) F12 888 F4. - F5 F7 FB F9 F10 :95 F1 X @ # dele 8 2 3 5 6STP 231 2022 Spring B 20713 Tran (1) Maryana Tymkiv 04/27/22 6:22 PM ? Homework: HW 19: Ch 10 - Bivariate Data and Question 7, 10.1.17-T Linear Correlati HW Score: 17.83%, 2.67 of 15 points Part 3 of 7 Points: 0 of 1 Save Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports 228 264 359 481 534 Crash Fatality Rate 15.8 15.7 15.4 15.3 14.8 What are the null and alternative hypotheses? O A. Ho: P#0 XB. Hip=0 H1: p =0 O C. Ho: P=0 *D. Ho: P=0 H, : p >0 H1: p#0 Construct a scatterplot. Choose the correct graph below. OA. X B C. AY 17- 17 1y 16- 16- 16- 15 15 15 o 14 200 400 600 200 400 600 200 400 600 200 600 The linear correlation coefficient is r = . (Round to three decimal places as needed.) Vi Vi (1,1) More Clear all Check answer Help me solve this View an example Get more help - MacBook Air 20 F3 888 F4 F5 -2- F6 44 F7 DII FB F9 F10 esc 295 FZ @ # O del 2 4 5 6 P W E R\fSTP 231 2022 Spring B 20713 Tran (1) Maryana Tymkiv 04/27/22 6:23 PM ? Homework: HW 19: Ch 10 - Bivariate Data and Question 9, 10.1.23-T HW Score: 17.83%, 2.67 of 15 points Linear Correlati Part 2 of 7 Points: 0 of 1 Save Media periodically discuss the issue of heights of winning presidential candidates and heights of their main opponents. The accompanying table lists the heights (cm) from several recent presidential elections. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should we expect that there would be a correlation? Use a significance level of of = 0.01. Click the icon to view the heights of the candidates. Construct a scatterplot. Choose the correct graph below. B XC DD. 5 200 it (cm) 5 200 Opponent Height (eng Opponent Height (cm) Opponent Height Opponent Height 60- 160- 160 200 200 160 200 160 President Height (cm) X The linear correlation coefficientis r = Candidate Heights (Round to three decimal places as needed.) President 183 186 190 177 179 185 198 186 173 182 190 192 182 184 Opponent 178 175 187 170 173 185 175 177 185 176 171 193 181 173 Print Done Help me solve this View an example Get more help - Clear all Check answer MacBook Air DII esc 295 F2 20 F3. 868 F4 F6 4 F7 FB DD FO F10 % 4 5 6 9 O